Forecasting the Amount of Based on a Regression Model with Lagged Variables
Keywords:
cash in circulation, monetary aggregate M0, econometric modelling, inflation, forecasting.Abstract
Despite the rather positive dynamics in developing the non-cash payment infrastructure, cash in Russia
has been and remains the widespread instrument of payment. The purpose of this paper is the development of a
model for forecasting the amount of cash in circulation in the country, namely the value of the monetary aggregate
M0, by the example of the Russian Federation. At the same time, the objectives were set so that the resulting
model should be suitable for a sufficiently accurate rapid estimation of М0 value, should be easy to use, and
should not be overloaded with many variables. The author succeeded in achieving these purposes in the
research using a formal approach based on a model with lagged variables, autoregression and time series
analysis, also using numerical methods. The lagged variables used were the inflation rate and the value of the
monetary aggregate for a previous period. The high quality, accuracy and forecasting power of the model are
substantiated. The average approximation error of the model did not exceed 5%.Testing of the model using
statistical data of the current year showed high accuracy of forecasting. Statistical data of official sources of the
Russian Federation were used for the model development.
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